A Deep Learning Framework for Design and Analysis of Surgical Bioprosthetic Heart Valves.

Journal: Scientific reports
Published Date: Dec 6, 2019

Abstract

Bioprosthetic heart valves (BHVs) are commonly used as heart valve replacements but they are prone to fatigue failure; estimating their remaining life directly from medical images is difficult. Analyzing the valve performance can provide better guidance for personalized valve design. However, such analyses are often computationally intensive. In this work, we introduce the concept of deep learning (DL) based finite element analysis (DLFEA) to learn the deformation biomechanics of bioprosthetic aortic valves directly from simulations. The proposed DL framework can eliminate the time-consuming biomechanics simulations, while predicting valve deformations with the same fidelity. We present statistical results that demonstrate the high performance of the DLFEA framework and the applicability of the framework to predict bioprosthetic aortic valve deformations. With further development, such a tool can provide fast decision support for designing surgical bioprosthetic aortic valves. Ultimately, this framework could be extended to other BHVs and improve patient care.

Authors

  • Aditya Balu
    Iowa State University, Department of Mechanical Engineering, Ames, Iowa, 50011, USA.
  • Sahiti Nallagonda
    Iowa State University, Department of Mechanical Engineering, Ames, Iowa, 50011, USA.
  • Fei Xu
    GeoHealth Initiative, Faculty of Geo-information Science and Earth Observation (ITC), University of Twente, Enschede, 7500, the Netherlands; International Initiative on Spatial Lifecourse Epidemiology (ISLE), the Netherlands; Nanjing Municipal Center for Disease Control and Prevention, Nanjing, Jiangsu, 210003, China; Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, 211100, China.
  • Adarsh Krishnamurthy
    Iowa State University, Department of Mechanical Engineering, Ames, Iowa, 50011, USA. adarsh@iastate.edu.
  • Ming-Chen Hsu
    Iowa State University, Department of Mechanical Engineering, Ames, Iowa, 50011, USA.
  • Soumik Sarkar
    Department of Mechanical Engineering, Iowa State University, Ames, IA, USA.

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